This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Back in 1934, Ralph Nelson Elliott discovered that price action displayed on charts, instead of behaving in a somewhat chaotic manner, had actually an intrinsic narrative attached. Elliot saw the same ...

An in-depth analysis of nutrient availability across mouse tissues reveals their influence on the spread of cancer to other organs. Measurements of the masses of exoplanets orbiting a young star have ...

Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples ...

Pupil dilation provides a physiological readout of information gain during the brain's internal process of belief updating in the context of associative learning.

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...

Optimism about its growing AI business gave the Google parent entry to a rarefied club. The move taps one of the most senior women on Wall Street and a former Trump adviser to help lead the company’s ...

Abstract: Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical ...

Abstract: Bayesian optimization (BO) is a framework for global optimization of expensive-to-evaluate objective functions. Classical BO methods assume that the objective function is a black box.